Identification of Rainfall Trends over Four Cities of Assam, India

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
R. Buragohain, H. Medhi, B. Kh. Narzary, K. U. Ahamad
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Abstract

In time-series analysis, several non-parametric and parametric techniques are available to identify a trend. However, due to the lesser sensitivity of the non-parametric methods towards the outliers, they are often given priority over parametric methods for analysing the trend. In this study, the significance of the trend in the rainfall data of the four cities: Guwahati, Tezpur, North Lakhimpur, and Dibrugarh in Assam is examined using the non-parametric Mann–Kendall method. The non-parametric Sen’s estimator method is used to estimate the magnitude of the significant trends for the four cities. The rainfall trend has been studied based on monthly, yearly, and seasonal observations. The results clearly show that there is no trend in the cities except for Dibrugarh, where an increasing rainfall trend is observed within 5% significance level. Based on the seasonal rainfall analysis, it is noted that the pre- and post-monsoon precipitation has a significant increasing trend, while no trend is seen during the monsoon period, which indicates an absence of significant change in the rainfall magnitude during the monsoon for the study period. The analysis of the monthly rainfall data has reveal a significant trend for July in the cities of Guwahati and Tezpur, which are closely located, while the significant trend for May is seen in the city of North Lakhimpur. However, for Dibrugarh, all months have shown significant trends at 5% except for September, November, and December. The analysis has shown that there is a significant change in the rainfall trend for the non-monsoon period, indicating the change in the rainfall pattern, while the overall trend for the monsoon period remains the same. This change of rainfall pattern during the non-monsoon period may be an impact of the climate change, which requires detailed studies. The overall analysis for the four sites over the period under review has shown a significant trend in rainfall only for Dibrugarh.

识别印度阿萨姆邦四个城市的降雨趋势
摘要 在时间序列分析中,有几种非参数和参数技术可用于确定趋势。然而,由于非参数方法对异常值的敏感性较低,因此在分析趋势时往往优先于参数方法。在本研究中,四个城市降雨量数据的趋势意义重大:本研究使用非参数 Mann-Kendall 方法研究了阿萨姆邦古瓦哈提、特兹布尔、北拉克林布尔和迪布吕赫四个城市降雨量数据趋势的重要性。非参数森氏估算器方法用于估算四个城市的显著趋势的大小。对降雨趋势的研究基于月度、年度和季节观测。结果清楚地表明,除了迪布勒格尔的降雨量在 5%的显著性水平内呈上升趋势外,其他城市的降雨量都没有趋势。根据季节性降雨量分析,季风前后的降雨量呈显著增加趋势,而季风期间则没有趋势,这表明研究期间季风期间的降雨量没有显著变化。对月降雨量数据的分析表明,古瓦哈提和特兹普尔两座城市的月降雨量在 7 月份呈显著上升趋势,而北拉克辛布尔市的月降雨量在 5 月份呈显著上升趋势。然而,就迪布鲁加尔而言,除 9 月、11 月和 12 月外,其他月份都呈现出 5%的显著趋势。分析表明,非季风期的降雨趋势有显著变化,表明降雨模式发生了变化,而季风期的总体趋势保持不变。非季风期降雨模式的变化可能是气候变化的影响,需要进行详细研究。对审查期间四个地点的总体分析表明,只有迪布勒格尔的降雨趋势显著。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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